This paper provides a survey of six widely used non-experimental methods for estimating the impact of programmes in the context of developing economies (instrumental variables, regression discontinuity, direct matching, propensity score matching, linear regression and non-parametric methods, and...

Since interventions by the public sector generally commit substantial societal resources, the evaluation of effects and costs of policy interventions is imperative. This paper outlines why program evaluation should follow well-respected scientific standards and why it should be performed by...

This paper provides a preliminary assessment of recent reforms of German employment promotion policy. While several recent studies analyze the impact of measures of employment promotion for the case of Germany, no comparable study exists on the aggregate level, thus precluding any assessment of...

The context of community-based interventions presents formidable problems for any evaluation analysis. Group-randomized studies do possess ideal properties in theory, but in practice, grouprandomization might not be a feasible alternative at all or group-randomized studies might be contaminated....

Large-scale environmental programs generally commit substantial societal resources, making the evaluation of their actual effects on the relevant outcomes imperative. As the example of the subsidization of energy-saving appliances illustrates, much of the applied environmental economics...

Large-scale environmental programs generally commit substantial societal resources, making the evaluation of their actual effects on the relevant outcomes imperative. As the example of the subsidization of energy-saving appliances illustrates, much of the applied environmental economics...

We study unrepresentative observational data in survival analysis. The first paper focuses on proportional hazards regressionwhen observed subjects have different selection probabilities. Wedevelop methods which are applicable when the selectionprobabilities are unknown but estimated using...

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....

Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....

Purpose: The purpose of this article is to better understand the management challenges facing managers in small growing firms. Design/methodology/approach: Empirical data have been collected in Sweden through structured observations (approx. 20,000 min) of the working days of six top managers in...